Edge computing is shaping up as the most practical way to manage the growing volume of data being generated by remote sources such as IoT and 5G devices.A key benefit of edge computing is that it provides greater computation, network access, and storage capabilities closer to the source of the data, allowing organizations to reduce latency. As a result, enterprise are embracing the model: Gartner estimates that 50% of enterprise data will be generated at the edge by 2023, and PricewaterhouseCoopers predicts the global market for edge data centers will reach $13.5 billion in 2024, up from $4 billion in 2017. To read this article in full, please click here
Home workers deserve the same level of network reliability as their on-site counterparts. Fortunately, reaching this goal is probably easier than you think.
As artificial intelligence grows increasingly powerful and reliable, some IT professionals worry that the technology could gradually make their jobs less meaningful and relevant.
Nothing lasts forever, including stored data. Here's how to ensure that your organization's information infrastructure remains accurate and intact for a lifetime.
A step beyond network monitoring, network visibility technology provides deep insights into everything within and moving through your enterprise network.
COVID-19 forced many organizations to create virtual IT teams. Things worked out so well that a growing number of IT leaders are now looking to build a permanent home-based workforce.
AI tools are set to transform network management and operations. The technology is also poised to bring major changes to the way network leaders and staff work.
SD-WAN's days appear to be numbered. SASE promises to become the go-to networking technology for linking together virtually all types of users and devices.
As data center workloads spiral upward, a growing number of enterprises are looking to artificial intelligence (AI), hoping that technology will enable them to reduce the management burden on IT teams while boosting efficiency and slashing expenses.AI promises to automate the movement of workloads to the most efficient infrastructure in real time, both inside the data center as well as in a hybrid-cloud setting comprised of on-prem, cloud, and edge environments. As AI transforms workload management, future data centers may look far different than today's facilities. One possible scenario is a collection of small, interconnected edge data centers, all managed by a remote administrator.To read this article in full, please click here
As data center workloads spiral upward, a growing number of enterprises are looking to artificial intelligence (AI), hoping that technology will enable them to reduce the management burden on IT teams while boosting efficiency and slashing expenses.AI promises to automate the movement of workloads to the most efficient infrastructure in real time, both inside the data center as well as in a hybrid-cloud setting comprised of on-prem, cloud, and edge environments. As AI transforms workload management, future data centers may look far different than today's facilities. One possible scenario is a collection of small, interconnected edge data centers, all managed by a remote administrator.To read this article in full, please click here
As data center workloads spiral upward, a growing number of enterprises are looking to artificial intelligence (AI), hoping that technology will enable them to reduce the management burden on IT teams while boosting efficiency and slashing expenses.AI promises to automate the movement of workloads to the most efficient infrastructure in real time, both inside the data center as well as in a hybrid-cloud setting comprised of on-prem, cloud, and edge environments. As AI transforms workload management, future data centers may look far different than today's facilities. One possible scenario is a collection of small, interconnected edge data centers, all managed by a remote administrator.To read this article in full, please click here
As data center workloads spiral upward, a growing number of enterprises are looking to artificial intelligence (AI), hoping that technology will enable them to reduce the management burden on IT teams while boosting efficiency and slashing expenses.AI promises to automate the movement of workloads to the most efficient infrastructure in real time, both inside the data center as well as in a hybrid-cloud setting comprised of on-prem, cloud, and edge environments. As AI transforms workload management, future data centers may look far different than today's facilities. One possible scenario is a collection of small, interconnected edge data centers, all managed by a remote administrator.To read this article in full, please click here
As IT operations continue drifting into the cloud, it's important to ensure that organization personnel keep pace with the latest skills and practices.
Some IT staffers don't want to come back to the office, while others can't wait to return. Here's how IT leaders can plan for a split workforce in a post-pandemic workplace.
Despite providing generally fast and reliable remote security during the COVID-19 pandemic, VPN may soon be replaced by an even more resilient technology. Here's what you need to know about zero-trust security.
Soon after data centers began transitioning from hard drives to solid-state drives (SSD), the NVMe protocol arrived to support high-performance, direct-attached PCIe SSDs. NVMe was followed by NVMe over Fabrics (NVMe-oF), which was designed to efficiently support hyperscale remote SSD pools, effectively replacing direct-attached storage (DAS) to become the default protocol for disaggregated storage within a cloud infrastructure.To read this article in full, please click here
John Edwards